부산대학교 도서관

In this article, a data-driven multiple-input–multiple-output (MIMO) feedforward control approach is synthesized to enhance the tracking performance of precision MIMO motion systems. Specifically, a MIMO feedforward controller parameterized with polynomial basis functions is employed to address the coupling of MIMO systems. A new data-driven feedforward tuning algorithm for the MIMO feedforward controller is then developed based on the measured step response of the process sensitivity function. The proposed approach requires only one tracking experiment in each iteration, resulting in an experimentally efficient feedforward parameter optimization w.r.t. a user-defined and tracking-performance-related criterion through iterative learning from the measured data. Finally, application to an industrial three degrees-of-freedom motion stage illustrates that the proposed approach outperforms a data-driven single-input–single-output (SISO) feedforward control scheme in terms of tracking performance and achieves good performance robustness against the reference variation.